0pi-mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| create_objectA | Save objects to ephemeral cloud storage - Store your reasoning state, large JSON structures, or any data to get a shareable URL. Perfect for: caching contexts before token limits, bridging multi-agent workflows, storing intermediate results, sharing data between sessions, or temporary data storage. Returns a shareable URL valid for 2 hours with auto-expiring data. |
| get_objectA | Retrieve data from cloud storage using its ID. Use this to read data that another agent (or yourself) saved previously. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: create_object saves data to cloud storage and returns a URL, while get_object retrieves data from storage using an ID. There is no overlap or ambiguity between them.
Both tools follow a consistent verb_noun pattern (create_object and get_object), using the same naming convention throughout. This makes them predictable and easy to understand.
With only two tools, the server feels thin for its purpose of ephemeral cloud storage. While create and get cover basic operations, the lack of update, delete, or list tools limits functionality and may cause agent workarounds.
The tool surface is significantly incomplete for cloud storage. It supports create and get operations but lacks update, delete, list, or management tools, which are essential for a full storage lifecycle and will likely lead to agent failures in complex workflows.